Knowing what species inhabit an area is important for conservation and ecosystem management. It is also useful to know how common or rare each species might be, or how many species are threatened or endangered in a given area.
Species lists are a common tool to find what species are in a given area for monitoring and environmental impact assessments. Often, these lists are asked to be produced for specific regions like Local Government Areas (LGAs) or specific monitoring locations within a region.
In this post, we will show you how to generate a species list for an Local Government Area—the Yass Valley—over the past year in either Python or R.
Make a species list
There are two ways to narrow a query to return information for a specific region:
- Using fields available in
galah-python(downloaded from the ALA) - Using a shapefile
The method you choose depends on whether the region you wish to return species for is already within galah-python, or whether you require a list for a more specific area defined by a shapefile.
Let’s go through each of the methods in turn to return a list of species in the Yass Valley in 2023.
First, let’s import galah.
import galahUse an existing spatial field
Search for fields
Let’s find which fields and layers exist within galah-python to narrow our query to a specific LGA region and year.
We can use the search_all() function to search for many types of information in galah-python. Let’s use it to look up what fields contain the word “year”. Our search returns several options, though the best option seems to be the field id "year".
galah.search_all(fields="year") id description type link
0 year The year in which an occurrence was observed. ... field https://github.com/AtlasOfLivingAustralia/ala-...
1 endDayOfYear http://rs.tdwg.org/dwc/terms/endDayOfYear field NaN
2 datePrecision The precision of the date information for the ... field NaN
3 occurrenceYear Year ranges for a search. Calculated based on ... field NaN
4 startDayOfYear http://rs.tdwg.org/dwc/terms/startDayOfYear field NaN
5 namePublishedInYear http://rs.tdwg.org/dwc/terms/namePublishedInYear field NaNTo double check whether a given field contains the information we are interested in, we can use show_values() to see what values are within the "year".
galah.show_values(field="year") field category
0 year 2022
1 year 2021
2 year 2020
3 year 2019
4 year 2018
.. ... ...
280 year 1755
281 year 1756
282 year 1762
283 year 1763
284 year 1764
[285 rows x 2 columns]Let’s use the same process to search for a field containing spatial data of Local Government Areas. Our search returns a few options.
galah.search_all(fields="Local Government Areas") id description type link
0 cl23 Local Government Areas 2012 deprecated LGA Bou... layers
1 cl959 Local Government Areas 2011 Local Government A... layers
2 cl2012 NSW Local Land Services Regions NSW Local Land... layers
3 cl10923 Local Government Areas PSMA 2018 Local Governm... layers The field cl10923 seems to be contain the most recent data from 2018. Let’s check what this values this field contains.
galah.show_values(field="cl10923") field category
0 cl10923 BRISBANE CITY
1 cl10923 EAST GIPPSLAND SHIRE
2 cl10923 GREATER GEELONG CITY
3 cl10923 PASTORAL UNINCORPORATED AREA
4 cl10923 MORETON BAY REGIONAL
.. ... ...
555 cl10923 WAGAIT SHIRE
556 cl10923 WOORABINDA ABORIGINAL SHIRE
557 cl10923 WUJAL WUJAL ABORIGINAL SHIRE
558 cl10923 CHERBOURG ABORIGINAL SHIRE
559 cl10923 BELYUEN SHIRE
[560 rows x 2 columns]We can use search for the value “Yass Valley” specifically with search_values().
galah.search_values(field="cl10923", value = "YASS VALLEY") field category
0 cl10923 YASS VALLEY COUNCIL
Note
Each spatial layer has a two letter code, along with a number to identify it. The abbreviations are as follows:
cl= contextual layer (i.e. boundaries of LGAs, Indigenous Protected Areas, States/Territories etc.)
10923= number associated with the spatial layer in the atlas
Download data
Now we can build a query to return species observed in Yass Valley over 2023. We can use atlas_species() to return a species list, and use the filters argument to narrow our query.
galah.atlas_species(filters=["year=2023","cl10923=YASS VALLEY COUNCIL"]) Species Species Name Scientific Name Authorship Taxon Rank Kingdom Phylum Class Order Family Genus Vernacular Name
0 https://biodiversity.org.au/afd/taxa/5291343e-... Gymnorhina tibicen (Latham, 1801) species Animalia Chordata Aves Passeriformes Artamidae Gymnorhina Australian Magpie
1 https://biodiversity.org.au/afd/taxa/97a59c84-... Rhipidura (Rhipidura) albiscapa Gould, 1840 species Animalia Chordata Aves Passeriformes Rhipiduridae Rhipidura Grey Fantail
2 https://biodiversity.org.au/afd/taxa/760401df-... Malurus (Malurus) cyaneus (Ellis, 1782) species Animalia Chordata Aves Passeriformes Maluridae Malurus Superb Fairy-wren
3 https://biodiversity.org.au/afd/taxa/2c33a1fd-... Cacatua (Cacatua) galerita (Latham, 1790) species Animalia Chordata Aves Psittaciformes Cacatuidae Cacatua Sulphur-crested Cockatoo
4 https://biodiversity.org.au/afd/taxa/5e0f496f-... Platycercus (Platycercus) elegans (Gmelin, 1788) species Animalia Chordata Aves Psittaciformes Psittacidae Platycercus Crimson Rosella
.. ... ... ... ... ... ... ... ... ... ... ...
823 https://id.biodiversity.org.au/taxon/apni/5141... Pterostylis jonesii G.N.Backh. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Pterostylis NaN
824 https://id.biodiversity.org.au/taxon/apni/5141... Pterostylis multiflora (D.L.Jones) G.N.Backh. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Pterostylis Mountain Brown-tip Greenhood
825 https://id.biodiversity.org.au/taxon/apni/5141... Pterostylis pedunculata R.Br. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Pterostylis Maroonhood
826 https://id.biodiversity.org.au/taxon/apni/5141... Thelymitra ixioides Sw. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Thelymitra Dotted Sun Orchid
827 https://id.biodiversity.org.au/taxon/ausmoss/1... Thuidiopsis sparsa (Hook.f. & Wilson) Broth. species Plantae Bryophyta Bryopsida Hypnales Thuidiaceae Thuidiopsis NaN
[828 rows x 11 columns]To add the observation count for each species, add counts=True.
species_yass = galah.atlas_species(filters=["year=2023","cl10923=YASS VALLEY COUNCIL"],counts=True)
species_yass Species Species Name Scientific Name Authorship Taxon Rank Kingdom Phylum Class Order Family Genus Vernacular Name Number of records
0 https://biodiversity.org.au/afd/taxa/5291343e-... Gymnorhina tibicen (Latham, 1801) species Animalia Chordata Aves Passeriformes Artamidae Gymnorhina Australian Magpie 332
1 https://biodiversity.org.au/afd/taxa/97a59c84-... Rhipidura (Rhipidura) albiscapa Gould, 1840 species Animalia Chordata Aves Passeriformes Rhipiduridae Rhipidura Grey Fantail 252
2 https://biodiversity.org.au/afd/taxa/760401df-... Malurus (Malurus) cyaneus (Ellis, 1782) species Animalia Chordata Aves Passeriformes Maluridae Malurus Superb Fairy-wren 249
3 https://biodiversity.org.au/afd/taxa/2c33a1fd-... Cacatua (Cacatua) galerita (Latham, 1790) species Animalia Chordata Aves Psittaciformes Cacatuidae Cacatua Sulphur-crested Cockatoo 238
4 https://biodiversity.org.au/afd/taxa/5e0f496f-... Platycercus (Platycercus) elegans (Gmelin, 1788) species Animalia Chordata Aves Psittaciformes Psittacidae Platycercus Crimson Rosella 201
.. ... ... ... ... ... ... ... ... ... ... ... ...
823 https://id.biodiversity.org.au/taxon/apni/5141... Pterostylis jonesii G.N.Backh. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Pterostylis NaN 1
824 https://id.biodiversity.org.au/taxon/apni/5141... Pterostylis multiflora (D.L.Jones) G.N.Backh. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Pterostylis Mountain Brown-tip Greenhood 1
825 https://id.biodiversity.org.au/taxon/apni/5141... Pterostylis pedunculata R.Br. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Pterostylis Maroonhood 1
826 https://id.biodiversity.org.au/taxon/apni/5141... Thelymitra ixioides Sw. species Plantae Charophyta Equisetopsida Asparagales Orchidaceae Thelymitra Dotted Sun Orchid 1
827 https://id.biodiversity.org.au/taxon/ausmoss/1... Thuidiopsis sparsa (Hook.f. & Wilson) Broth. species Plantae Bryophyta Bryopsida Hypnales Thuidiaceae Thuidiopsis NaN 1
[828 rows x 12 columns]To save this species list as a csv, we can use to_csv() from the pandas dataframe package.
species_yass.to_csv("Species_List_Yass_Valley_Counts_ALA_Spatial_Filter.csv")Shapefile
Download shapefile
Let’s download the latest Local Government Areas data from the Australian Bureau of Statistics Digital Boundary files page. Find “Local Government Areas - 2023 - Shapefile” and click “Download ZIP”. Save the zip folder in your current directory and unzip it.
We’ll use read_file() from geopandas to load our shapefile.
import geopandas as gpd
LGAs_2023 = gpd.read_file("LGA_2023_AUST_GDA2020.shp")
LGAs_2023 LGA_CODE23 LGA_NAME23 STE_CODE21 STE_NAME21 AUS_CODE21 AUS_NAME21 AREASQKM LOCI_URI21 geometry
0 10050 Albury 1 New South Wales AUS Australia 305.6386 https://linked.data.gov.au/dataset/asgsed3/LGA... POLYGON ((146.86566 -36.07292, 146.86512 -36.0...
1 10180 Armidale 1 New South Wales AUS Australia 7809.4406 https://linked.data.gov.au/dataset/asgsed3/LGA... POLYGON ((152.38816 -30.52639, 152.38812 -30.5...
2 10250 Ballina 1 New South Wales AUS Australia 484.9692 https://linked.data.gov.au/dataset/asgsed3/LGA... MULTIPOLYGON (((153.57106 -28.87381, 153.57106...
3 10300 Balranald 1 New South Wales AUS Australia 21690.7493 https://linked.data.gov.au/dataset/asgsed3/LGA... POLYGON ((143.00433 -33.78164, 143.01538 -33.7...
4 10470 Bathurst 1 New South Wales AUS Australia 3817.8645 https://linked.data.gov.au/dataset/asgsed3/LGA... POLYGON ((149.84877 -33.52784, 149.84864 -33.5...
.. ... ... ... ... ... ... ... ... ...
561 89799 Migratory - Offshore - Shipping (ACT) 8 Australian Capital Territory AUS Australia NaN https://linked.data.gov.au/dataset/asgsed3/LGA... None
562 99399 Unincorp. Other Territories 9 Other Territories AUS Australia 105.8806 https://linked.data.gov.au/dataset/asgsed3/LGA... MULTIPOLYGON (((167.94747 -29.12757, 167.94748...
563 99499 No usual address (OT) 9 Other Territories AUS Australia NaN https://linked.data.gov.au/dataset/asgsed3/LGA... None
564 99799 Migratory - Offshore - Shipping (OT) 9 Other Territories AUS Australia NaN https://linked.data.gov.au/dataset/asgsed3/LGA... None
565 ZZZZZ Outside Australia Z Outside Australia ZZZ Outside Australia NaN https://linked.data.gov.au/dataset/asgsed3/LGA... None
[566 rows x 9 columns]Now let’s use to_crs() to set the Coordinate Reference System (CRS) of our shapefile. A CRS refers to how coordinates on the spherical earth are oriented onto a flat, two-dimensional map. ALA observations are projected using WGS84 (the standard used in cartography and GPS), also known as EPSG:4326.
LGAs_2023 = LGAs_2023.to_crs(4326)
LGAs_2023.plot(edgecolor = "#5A5A5A", linewidth = 0.5, facecolor = "white", figsize = (12,5))
We’ll filter our shapefile to only Yass Valley.
The column LGA_NAME23 appears to contain names we can use to filter our Dataframe. Let’s filter LGA_NAME23 to return only the row containing Yass Valley.
yass_valley = LGAs_2023[LGAs_2023['LGA_NAME23'] == "Yass Valley"]
yass_valley LGA_CODE23 LGA_NAME23 STE_CODE21 STE_NAME21 AUS_CODE21 AUS_NAME21 AREASQKM LOCI_URI21 geometry
127 18710 Yass Valley 1 New South Wales AUS Australia 3995.017 https://linked.data.gov.au/dataset/asgsed3/LGA... POLYGON ((148.58152 -34.80679, 148.58153 -34.8...The column geometry contains information to draw our LGA shape. Let’s select just this column.
yass_valley["geometry"]127 POLYGON ((148.58152 -34.80679, 148.58153 -34.8...
Name: geometry, dtype: geometryNow that we have the polygon stored as yass_valley_geometry, we can pass it to the polygon argument of atlas_species(). We can also narrow our query to only 2023 observations by adding year to filters, and add the observation count of each species by addint counts=True.
